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Nabilla Saumi Putri
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Computer Science & IT

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Analisis sentimen review aplikasi mypertamina pada twitter menggunakan metode naïve bayes classifier Nabilla Saumi Putri
Computer Science and Information Technology Vol 4 No 1 (2023): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/coscitech.v4i1.4789

Abstract

Downstream and Natural Gas Regulatory Agency (BPH Migas) Pertamina launched the mypertamina application for subsidized fuel oil (BBM) such as pertalite and diesel which will then be used as a digital financial service that integrates with the link aja application to ensure the subsidised fuel distribution process is truly on target. The problem after the launch of the mypertamina application harvested many pros and cons, one of which was that the application was difficult to use, complicated to use as evidenced in the comments on Twitter. From this problem it can be used as a sentiment analysis research to find out positive comments and negative comments in the mypertamina application review. The naive Bayes classifier method was used in this study for the classification process. In this study using as many as 1001 tweet data from the data collection process sourced from Twitter consisting of 494 positive and 507 negative, in the naive Bayes classifier classification process the accuracy value is 71% with 90% training data and 10% test data
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